mwavepy.parameterizedStandard | index /usr/local/lib/python2.6/dist-packages/mwavepy/parameterizedStandard.py

`provides Parameterized Standard class.`

Modules
`` |  |
numpy | pylab |  |

Classes
`` |  | __builtin__.object ParameterizedStandard DelayLoad_Mulipath DelayShort_Mulipath DelayedShort_TranslationMissalignment DelayedShort_UnknownLength DelayedTermination_TranslationMissalignment DelayedTermination_UnknownLength DelayedTermination_UnknownLength_TranslationMissalignment DelayedTermination_UnknownLength_UnknownTermination DelayedTermination_UnknownTermination Line_TranslationMissalignment Line_UnknownLength Line_UnknownLength_TranslationMissalignment Match_TranslationMissalignment Parameterless RotatedWaveguide_UnknownLength SlidingLoad_UnknownTermination Thru_TranslationMissalignment exceptions.Exception(exceptions.BaseException) ParameterBoundsError
class DelayLoad_Mulipath(ParameterizedStandard)
`` | `A delay short of unknown length initial guess for length should be given to constructor`
| Method resolution order: DelayLoad_Mulipath ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d1, Gamma0, d2, d1_to_d2_power, **kwargs) `takes: wb: a WorkingBand type d: initial guess for delay short physical length [m] **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class DelayShort_Mulipath(ParameterizedStandard)
`` | `A delay short of unknown length initial guess for length should be given to constructor`
| Method resolution order: DelayShort_Mulipath ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d1, d2, d1_to_d2_power, **kwargs) `takes: wb: a WorkingBand type d: initial guess for delay short physical length [m] **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class DelayedShort_TranslationMissalignment(ParameterizedStandard)
`` | `A delayed rectangular waveguide termination with unknown flange translation missalignment.`
| Method resolution order: DelayedShort_TranslationMissalignment ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, initial_offset=0.10000000000000001, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: distance to termination Gamma0: reflection coefficient off termination at termination initial_offset: initial offset guess, as a fraction of a, (the waveguide width dimension) **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class DelayedShort_UnknownLength(ParameterizedStandard)
`` | `A delay short of unknown length initial guess for length should be given to constructor`
| Method resolution order: DelayedShort_UnknownLength ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, **kwargs) `takes: wb: a WorkingBand type d: initial guess for delay short physical length [m] **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class DelayedTermination_TranslationMissalignment(ParameterizedStandard)
`` | `A delayed rectangular waveguide termination with unknown flange translation missalignment.`
| Method resolution order: DelayedTermination_TranslationMissalignment ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, Gamma0, initial_offset=0.10000000000000001, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: distance to termination Gamma0: reflection coefficient off termination at termination initial_offset: initial offset guess, as a fraction of a, (the waveguide width dimension) **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class DelayedTermination_UnknownLength(ParameterizedStandard)
`` | `A Delayed Termination of unknown length, but known termination`
| Method resolution order: DelayedTermination_UnknownLength ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, Gamma0, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: distance to termination Gamma0: reflection coefficient off termination at termination **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class DelayedTermination_UnknownLength_TranslationMissalignment(ParameterizedStandard)
`` | `A known Delayed Termination with unknown translation missalignment. the initial guess for missalignment defaults to [1/10,1/10]*a, where a is the waveguide width`
| Method resolution order: DelayedTermination_UnknownLength_TranslationMissalignment ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, Gamma0, initial_offset=0.10000000000000001, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: distance to termination Gamma0: reflection coefficient off termination at termination initial_offset: initial offset guess, as a fraction of a, (the waveguide width dimension) **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class DelayedTermination_UnknownLength_UnknownTermination(ParameterizedStandard)
`` | `A Delayed Termination of unknown length or termination`
| Method resolution order: DelayedTermination_UnknownLength_UnknownTermination ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, Gamma0, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: distance to termination Gamma0: reflection coefficient off termination at termination **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class DelayedTermination_UnknownTermination(ParameterizedStandard)
`` | `A Delayed Termination of unknown length or termination`
| Method resolution order: DelayedTermination_UnknownTermination ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, Gamma0, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: distance to termination Gamma0: reflection coefficient off termination at termination **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class Line_TranslationMissalignment(ParameterizedStandard)
`` | `A rectangular waveaguide matched line standard with unknown flange translation missalignment.`
| Method resolution order: Line_TranslationMissalignment ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, initial_offset=0.10000000000000001, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: length of line [m] Gamma0: reflection coefficient off termination at termination initial_offset: initial offset guess, as a fraction of a, (the waveguide width dimension) **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class Line_UnknownLength(ParameterizedStandard)
`` | `A matched delay line of unknown length initial guess for length should be given to constructor`
| Method resolution order: Line_UnknownLength ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, **kwargs) `takes: wb: a WorkingBand type d: initial guess for line length [m] **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class Line_UnknownLength_TranslationMissalignment(ParameterizedStandard)
`` | `A rectangular waveaguide matched line standard with unknown flange translation missalignment and unknown length.`
| Method resolution order: Line_UnknownLength_TranslationMissalignment ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, initial_offset=0.10000000000000001, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: guess for length of line [m] Gamma0: reflection coefficient off termination at termination initial_offset: initial offset guess, as a fraction of a, (the waveguide width dimension) **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class Match_TranslationMissalignment(ParameterizedStandard)
`` | `A match with unknown translation missalignment. the initial guess for missalignment is [a/10,a/10], where a is the waveguide width`
| Method resolution order: Match_TranslationMissalignment ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, initial_offset=0.10000000000000001, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. initial_offset: initial offset guess, as a fraction of a, (the waveguide width dimension) **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class ParameterBoundsError(exceptions.Exception)
`` |  | Method resolution order: ParameterBoundsError exceptions.Exception exceptions.BaseException __builtin__.object Data descriptors defined here: __weakref__ `list of weak references to the object (if defined)` Methods inherited from exceptions.Exception: __init__(...) `x.__init__(...) initializes x; see x.__class__.__doc__ for signature` Data and other attributes inherited from exceptions.Exception: __new__ = <built-in method __new__ of type object> `T.__new__(S, ...) -> a new object with type S, a subtype of T` Methods inherited from exceptions.BaseException: __delattr__(...) `x.__delattr__('name') <==> del x.name` __getattribute__(...) `x.__getattribute__('name') <==> x.name` __getitem__(...) `x.__getitem__(y) <==> x[y]` __getslice__(...) `x.__getslice__(i, j) <==> x[i:j] Use of negative indices is not supported.` __reduce__(...) __repr__(...) `x.__repr__() <==> repr(x)` __setattr__(...) `x.__setattr__('name', value) <==> x.name = value` __setstate__(...) __str__(...) `x.__str__() <==> str(x)` __unicode__(...) Data descriptors inherited from exceptions.BaseException: __dict__ args message
class ParameterizedStandard(__builtin__.object)
`` |  | Methods defined here: __init__(self, function=None, parameters={}, parameter_bounds={}, **kwargs) `takes: function: a function which will be called to generate a Network type, to be used as a ideal response. parameters: an dictionary holding an list of parameters, which will be the dependent variables to optimize. these are passed to the network creating function. **kwargs: keyword arguments passed to the function, but not used in parametric optimization.` Data descriptors defined here: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class Parameterless(ParameterizedStandard)
`` | `A parameterless standard. note: this is needed so that the calibration algorithm doesnt have to handle more than one class type for standards`
| Method resolution order: Parameterless ParameterizedStandard __builtin__.object Methods defined here: __init__(self, ideal_network) `takes: ideal_network: a Network instance of the standard` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class RotatedWaveguide_UnknownLength(ParameterizedStandard)
`` | `A rotated waveguide of unkown delay length.`
| Method resolution order: RotatedWaveguide_UnknownLength ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d, Gamma0, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: distance to termination Gamma0: reflection coefficient off termination at termination initial_offset: initial offset guess, as a fraction of a, (the waveguide width dimension) **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class SlidingLoad_UnknownTermination(ParameterizedStandard)
`` | `A set of parametersized standards representing a set of Delayed Terminations of known length, but unknown termination`
| Method resolution order: SlidingLoad_UnknownTermination ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, d_list, Gamma0, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d_list: list of distances to termination [m] Gamma0: guess for reflection coefficient off termination at termination **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`
class Thru_TranslationMissalignment(ParameterizedStandard)
`` | `A rectangular waveaguide thru standard with unknown flange translation missalignment.`
| Method resolution order: Thru_TranslationMissalignment ParameterizedStandard __builtin__.object Methods defined here: __init__(self, wb, initial_offset=0.10000000000000001, **kwargs) `takes: wb: a WorkingBand type, with a RectangularWaveguide object for its tline property. d: distance to termination Gamma0: reflection coefficient off termination at termination initial_offset: initial offset guess, as a fraction of a, (the waveguide width dimension) **kwargs: passed to self.function` Data descriptors inherited from ParameterizedStandard: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)` network `a Networks instance generated by calling function(), for the current set of parameters (and kwargs)` number_of_parameters `the number of parameters this standard has` parameter_array `This property provides a 1D-array interface to the parameters dictionary. This is needed to intereface teh optimizing function because it only takes a 1D-array. Therefore, order must be preserved with accessing and updating the parameters through this array. To handle this I make it return and update in alphebetical order of the parameters dictionary keys.` parameter_bounds_array `This property provides a 1D-array interface to the parameters bounds dictionary. if key doesnt exist, then i presume the parameter has no bounds. this then returns a tuple of -INF,INF where INF is a global variable in this class.` parameter_keys `returns a list of parameter dictionary keys in alphabetical order` s `a direct access to the calulated networks' s-matrix`

Functions
`` |  | zeros(...) `zeros(shape, dtype=float, order='C') Return a new array of given shape and type, filled with zeros. Parameters ---------- shape : {tuple of ints, int} Shape of the new array, e.g., ``(2, 3)`` or ``2``. dtype : data-type, optional The desired data-type for the array, e.g., `numpy.int8`. Default is `numpy.float64`. order : {'C', 'F'}, optional Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) order in memory. Returns ------- out : ndarray Array of zeros with the given shape, dtype, and order. See Also -------- numpy.zeros_like : Return an array of zeros with shape and type of input. numpy.ones_like : Return an array of ones with shape and type of input. numpy.empty_like : Return an empty array with shape and type of input. numpy.ones : Return a new array setting values to one. numpy.empty : Return a new uninitialized array. Examples -------- >>> np.zeros(5) array([ 0., 0., 0., 0., 0.]) >>> np.zeros((5,), dtype=numpy.int) array([0, 0, 0, 0, 0]) >>> np.zeros((2, 1)) array([[ 0.], [ 0.]]) >>> s = (2,2) >>> np.zeros(s) array([[ 0., 0.], [ 0., 0.]]) >>> np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) array([(0, 0), (0, 0)], dtype=[('x', '<i4'), ('y', '<i4')])`

Data
`` |  | INF = 1000000000000.0 micron = 9.9999999999999995e-07 mil = 2.5399999999999997e-05 pi = 3.1415926535897931 sin = <ufunc 'sin'>